Agent OS · Component · conversation-trace-curation
Redacted conversation trace capture
What it does
Build schema-validated conversation traces, apply redaction and mark eligibility/fallback status for future distillation datasets.
Core pattern
Conversation redaction + training candidate eligibility checks
- Input
- Conversation messages and composition metadata
- Output
- Redacted trace candidate or rejection with reasons
Key parameters
| Name | Type | Default | Values |
|---|---|---|---|
| operation | string | capture | capture · redact · validate · extract_features |
| trace | object | — | — |
| redaction_policy | object | — | — |
| policy | — | — | — |
| review_decision | — | — | — |
Maturity and limits
Capture/redaction/schema modules and explicit trainingEligible/usedFallback fields; no training loop evidenced. Phase 2: source paths and implementation inspected statically; tests and external integrations were not executed. Maturity rates repository implementation, not a verified production deployment.
No root reuse license found; user conversations, memory and real-person profiles are sensitive; current local SQLite/ops boundaries need hardening for multi-tenant deployment. Eligibility metadata does not replace user consent or establish model-training rights.
1 sentence citing source paths or vendor names omitted for publication.
Used in pipelines
Industry tags
- Lifestyle & consumer appsSource-supported industry
For work involving opt-in interactions, digital services and personal preferences, use conversation redaction followed by training candidate eligibility checks.
- EducationTransferable use
For sample acceptance checks before releasing a course question assistant, use conversation redaction followed by training candidate eligibility checks.
Skills pack
Contract scaffold and deterministic mock
Download · 11KBSHA-256 db1801be93ea95fdac9c3756ac1936012394c8a5cc179c21ce928f26e0434d05
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